Since 1999 Geokinetics has been providing depth imaging services to the oil and gas industry. Our Depth Imaging Team has completed projects in all parts of the world including the Gulf of Mexico, Latin America and West Africa.
Although our depth imaging solutions are tailored to specific geological or geophysical constraints (high dip, subsalt, complex geology/velocity, acquisition geometry effects, etc.), our emphasis is on ensuring that the best quality data possible is input to the depth imaging process. Geokinetics’ philosophy of depth imaging can be simply stated as “a depth migration can only be as good as the time processing that preceded it.” Utilizing this philosophy, our depth imaging team interacts with our processing geophysicists and our clients to assure that the time processing product is of the highest quality before model building begins.
Geokinetics has a full suite of depth migration technology, including our own proprietary Pre-Stack Depth Migration algorithms. We utilize the latest in Linux cluster technology to provide a superior depth product at a very competitive price.
SOLUTIONS DRIVEN / TECHNOLOGY FOCUSSED
Velocity Model Building
Building a velocity model for depth imaging is tremendously challenging. Because the solution is non-unique, both experience and a flexible and dynamic model building tool are paramount for fast, efficient and accurate velocity modeling.
Geokinetics uses two external software packages for velocity model building for pre-stack depth migration: Paradigm GeoDepth and dGB’s OpendTect – VMB. Both packages allow for robust velocity analysis, updating and integration of various geologic constraints. All 3D depth migration projects require a detailed 3D interval velocity model as input. The model building process involves making an initial estimate of interval velocities for each layer in the model, followed by iterative refinement of the model velocities and layer thicknesses until residual moveout has been minimized on depth migrated gathers.
Model refinements can be a vertical updating process, layer or grid tomography or a combination of both. Depth migrations performed during the model refinement stage can be either Kirchhoff target line migrations or full volume GSP migrations. Please contact us to find out more about our methods and strategies:
- Updating strategies
- Wave equation
This efficient, amplitude-friendly algorithm may be used for either target-oriented or full volume pre-stack migration where accurate images are required in areas of significant lateral velocity variation. In addition, it is especially useful in azimuthal analysis of wide and multiple azimuth datasets utilizing vector offsets and vector tiles.
The Kirchhoff depth algorithm operates in the time-space domain using a numerical approximation to the Kirchhoff integral description of the recorded wave field. A choice of ray paths is available for building traveltime tables and the algorithm incorporates temporal and spatial anti-alias protection as well as dip and aperture control. Amplitude integrity is maintained by a variety of weighting functions which compensate for geometric spreading and acquisition irregularities.
Specular Beam Imaging
Specular beam depth migration, “SBDM”, allows fast velocity model building and enhanced pre-stack depth imaging for 2D and 3D data in high noise areas. It is particularly effective in areas with high impedance overburdens like basalt, carbonates or salt, or in areas with pervasive scattering layers such as rugose beds, interbed stratigraphic complexity, conglommeratic fill, or fractured layers.
The algorithm utilizes a 3D pre-imaging scan to decompose events in the offset domain. Each event is characterized by a wavelet kernel, its 3D dip and its coherency. By raytracing a velocity model, the extracted event can be placed into its proper migrated position and the image reconstructed based on the decomposed dips. Because only coherent events are imaged, the reconstruction process is more efficient than a conventional Kirchhoff. In addition, because only coherent dips are imaged, events in high noise areas are better defined and more continuous.
This approach compares favorably to the common-reflection-surface, CRS, stack. The specular beam images give the same boost to signal-to-noise as the CRS approach with the benefit of allowing model updates using traditional velocity model building tools.
GSP+ one-way wave equation
The Generalised Screen Propagator is a wave theory approach which incorporates a finite difference term to ensure optimum focusing of high dip events at each downward continuation depth step. The algorithm is highly efficient, using a narrow, rather than common, azimuth assumption that enables this migration to be used in the model-building phase. It can be applied in either a common-offset domain or a shot domain implementation. This flexibility makes it suitable for many different acquisition geometries from land to wide-azimuth marine.
Our GSP+ migration will image energy arrivals from all travel paths and will correctly handle all wavelet phase and frequency amplitudes as well as providing alias protection. Unlike raytrace based methods, the accuracy and stability of the GSP approach allows the algorithm to more precisely honor the velocity model. Consequently the output image provides sharper detail, crisper faults and better focused geologic structures.
GSP+ is our recommended algorithm when amplitude preservation in complex settings with large velocity contrasts, particularly sub-salt regimes, is paramount. It is also particularly beneficial when rugose surfaces need to be defined or in fault shadow imaging where the subtle velocity variations across the faults must be maintained.
RTM two-way wave equation
Anisotropic VTI imaging
All of our imaging algorithms handle anisotropy using the Thomsen parameters delta and epsilon. Raytrace travel times are computed using weak elastic anisotropy while our GSP VTI algorithms use a propagator to accommodate the Thomsen parameters. The propagator is highly accurate and efficient, capable of handling large anisotropy heterogeneity even at large angles.